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Network Reconfiguration Framework for CO 2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms

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  • Wei-Chen Lin

    (Department of Industrial Education and Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Road, Changhua 500, Taiwan)

  • Chao-Hsien Hsiao

    (Department of Industrial Education and Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Road, Changhua 500, Taiwan)

  • Wei-Tzer Huang

    (Department of Industrial Education and Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Road, Changhua 500, Taiwan)

  • Kai-Chao Yao

    (Department of Industrial Education and Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Road, Changhua 500, Taiwan)

  • Yih-Der Lee

    (National Atomic Research Institute, Taoyuan 325, Taiwan)

  • Jheng-Lun Jian

    (National Atomic Research Institute, Taoyuan 325, Taiwan)

  • Yuan Hsieh

    (Department of Industrial Education and Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Road, Changhua 500, Taiwan)

Abstract

This paper presents the development of a generic active distribution network (ADN) operation simulation framework that incorporates selected swarm optimization algorithms (SOAs) for the purpose of reducing CO 2 emissions and line loss minimization through network reconfiguration (NR). The framework has been implemented in the ADN of Taipower. Network data, provided by the Distribution Mapping Management System and Distribution Dispatch Control Center (DDCC) of Taipower, were converted into an OpenDSS script to create ADN models. The SOA is integrated into the framework and utilized to determine the statuses of both four-way and two-way switches in the planning and operating stages, in accordance with the proposed multi-objective function and operational constraints. The weightings for these decisions can be customized by distribution operators to meet their specific requirements. In this paper, the weighting for line loss reduction is set to one for minimizing CO 2 emissions. The numerical results demonstrate that the proposed ADN framework can recommend a feeder switching scheme to distribution operators, aiming to balance feeder loading and minimize the neutral line current. Finally, this approach leads to reduced line losses and minimizes CO 2 emissions. In contrast to relying solely on historical operational experience, this generic ADN reconfiguration framework offers a systematic approach that can significantly contribute to reducing CO 2 emissions and enhancing the operational efficiency of ADNs.

Suggested Citation

  • Wei-Chen Lin & Chao-Hsien Hsiao & Wei-Tzer Huang & Kai-Chao Yao & Yih-Der Lee & Jheng-Lun Jian & Yuan Hsieh, 2024. "Network Reconfiguration Framework for CO 2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms," Sustainability, MDPI, vol. 16(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1493-:d:1336692
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    References listed on IDEAS

    as
    1. Yanmin Wu & Jiaqi Liu & Lu Wang & Yanjun An & Xiaofeng Zhang, 2023. "Distribution Network Reconfiguration Using Chaotic Particle Swarm Chicken Swarm Fusion Optimization Algorithm," Energies, MDPI, vol. 16(20), pages 1-17, October.
    2. Xin Yan & Qian Zhang, 2023. "Research on Combination of Distributed Generation Placement and Dynamic Distribution Network Reconfiguration Based on MIBWOA," Sustainability, MDPI, vol. 15(12), pages 1-34, June.
    3. Muthukumar Kandasamy & Renugadevi Thangavel & Thamaraiselvi Arumugam & Jayachandran Jayaram & Wook-Won Kim & Zong Woo Geem, 2022. "Performance Enhancement of Radial Power Distribution Networks Using Network Reconfiguration and Optimal Planning of Solar Photovoltaic-Based Distributed Generation and Shunt Capacitors," Sustainability, MDPI, vol. 14(18), pages 1-36, September.
    4. Dhivya Swaminathan & Arul Rajagopalan & Oscar Danilo Montoya & Savitha Arul & Luis Fernando Grisales-Noreña, 2023. "Distribution Network Reconfiguration Based on Hybrid Golden Flower Algorithm for Smart Cities Evolution," Energies, MDPI, vol. 16(5), pages 1-24, March.
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